Stochastic Gene Expression Effects in a Model Retrovirus

描述（由申请人提供）：在本提案中，我们寻求对HIV-1慢病毒模型中的基因表达动力学进行严格的实验和计算分析。慢病毒系统源自HIV-1，但保留了tat介导的控制转录活性的正反馈回路。这种反馈回路基序是所有生物体和细胞子系统中常见的基因调控结构，因此本研究得出的测量结果和结论将广泛适用。基于该系统的物理化学原理和简单模型，我们假设（并展示了初步实验结果）该系统的基因表达是高度随机的，并且tat介导的反馈是零星激活的，因此在病毒感染其靶细胞并整合到宿主基因组后，在病毒表达达到可发生繁殖并随后繁殖的点之前可能经过了很长一段时间。这段时间足以让激活的t细胞过渡到记忆状态，从而将慢病毒困在非活性状态，直到记忆细胞被重新激活。因此，有可能这种假设的噪音足够大，导致病毒潜伏池的形成，使HIV-1如此难以治疗。然而，这种可能性的实验证据很少，而且从未有严格的证据表明哺乳动物基因表达具有显著的随机性。因此，我们制定了一个计划，定量测量这个慢病毒、基于HIV-1的自激活基因表达系统中关键步骤的整合点依赖动力学。我们使用特殊设计的病毒结构与表达荧光标记和定量显微镜技术梳理出真核基因表达模型的所有参数。我们使用这些模型来估计过程中每个步骤的作用，从整合点到转录起始，到tar的延伸控制，到Tat的产生/降解，再到Tat/tar在表达过程中产生噪音并允许延迟直到病毒产生。我们还使用模型与数据的比较来确定哪些参数不受优化约束，从而直接测量。由此产生的实验验证的哺乳动物病毒基因表达模型将为其他人研究真核细胞过程中噪声的动力学和作用提供资源。

DESCRIPTION (provided by applicant): In this proposal we seek to perform a rigorous experimental and computational analysis of the dynamics of gene expression in a lentiviral model of HIV-1. The lentiviral system is derived from HIV-1 but leaves the Tat-mediated positive feedback loop controlling transcriptional activity intact. This feedback loop motif is a common gene regulatory architecture across all organisms and cellular subsystems thus measurements and conclusions derived from this study will apply broadly. Based on physical chemical principles and simple models of the system, we hypothesize (and show initial experimental results) that gene expression from this system is highly stochastic and that the Tat-mediated feedback is activated sporadically such that after the virus infects its target cell and integrates into the host genome, there may be significant periods of time elapsed before viral expression reaches the point where reproduction can occur and then propagate. This time could be enough to allow an activated T-cell to transition to its memory state thereby trapping the lentivirus in an inactive form until such time as that memory cell is reactivated. Thus, it is possible that this hypothesized noise is large enough to contribute to the formation of the latent pool of virus that makes HIV-1 so hard to treat. However, there is little experimental evidence of this possibility and further it has never been rigorously shown that mammalian gene expression is significantly stochastic. We therefore set out a program for quantitatively measuring the integration-point dependent kinetics of the key steps in this lentiviral, HIV-1 based, autoactivated gene expression system. We use specially designed viral constructs with fluorescent markers of expression and quantitative microscopy techniques to tease out all the parameters for a model of the eukaryotic gene expression model. We use the models to estimate the role of each of the steps in the process from integration point, to transcription initiation, to elongation control by tar, to Tat production/ degradation, to Tat/tar interaction in generating noise in the expression process and allowing delays until viral production. We also use the comparison of models to data to determine which parameters are not constrained by optimizations and thus direct measurements. The resultant experimentally-validated model of mammalian viral gene expression will be a resource for others studying the kinetics and role of noise in eukaryotic cellular processes.